Target tracking is the process of calculating the path or track of a moving object by monitoring its current position and using the data obtained from this monitoring to project its future position. An example of target tracking is the process of air traffic control where radar stations send out signals and receive back reflections (referred to as hits) from on-coming planes (targets), thereby determining the flight path (track) of the plane. The radar stations are referred to as active sensors since they originate the signals. Target tracking can also be performed using passive sensors. In this type of tracking, the sensors receive signals (referred to as results or returns) sent out by the targets to be tracked. Satellite observation sensors, which sense infrared rays, are a common example of passive sensors.
In many practical applications, signals may be reflected back (or sent out from) objects other than the target being tracked. For example, if the target is an extremely low flying plane, signals may be reflected back from objects on the ground. In the case of orbital satellites, there may be other heat sources in the area in addition to the target tracked. These spurious reflections or returns from other than the tracked target are referred to as "clutter." It is a known problem in the art to distinguish clutter from valid hits. Clearly, if the clutter is erroneously believed to be valid data, that is, reflections from the tracked target, and input into the process used to project the target's future position, the projected results could diverge significantly from the actual path of the target.
It was known in the prior art that clutter could sometimes be distinguished from the target data by analyzing the signals from multiple stations. In practice, however, it was rare than there were enough stations in the proper position to provide the required cross triangulations. Other methods, useful if Doppler radar was used in tracking, relied on the Doppler shift frequency to track targets in the presence of clutter. (See, for example, Method of Tracking Target in Presence of Clutter, U.S. Pat. No. 4,559,537, E.C. Pearson, et al.)
Neither of these approaches was useful, however, in a situation in which the tracking was done by satellites. In the prior art, satellite tracking was done primarily by line of sight observations taken simultaneously from two satellites. FIG. 1 illustrates this approach. In the diagram, two satellites, A and B, simultaneously scan target T. The "return" or data received by the satellite is comprised of the infrared waves given off by target T. On a simplistic level, each satellite receives data comprised of the angle formed by some arbitrary base line (generally, the line which extends from the center of the Earth (C) to satellite) and the tracked object. For example, in FIG. 1, satellite A's data is comprised of angle 1 and satellite B's data is comprised of angle 2. Thus, the position of target T can be calculated by calculating the intersection point of the two simultaneous lines of sight observations (with angles 1 and 2) from the satellites.
Since the total cost of the satellite, its launch and its ground station are significant, the number of satellite observation bases available for any given application is relatively few. Thus, an approach which relies on multiple observations from multiple sensors to distinguish clutter is not, generally, viable. Since satellites are, generally, passive sensors with relatively long time lags between observations or scans (of the order of 10 seconds or more), using multiple observations from the same satellite was not viable. By the same token, Doppler shift analysis was generally not applicable in the passive sensor environment.